PREDICT_SVM_CLASSIFIER
Uses an SVM model to predict class labels for samples in an input relation, and returns the predicted value as a FLOAT data type.
Uses an SVM model to predict class labels for samples in an input relation, and returns the predicted value as a FLOAT data type.
Syntax
PREDICT_SVM_CLASSIFIER (input-columns
USING PARAMETERS model_name = 'model-name'
[, match_by_pos = match-by-position]
[, type = 'return-type']
[, cutoff = 'cutoff-value'] ] )
Arguments
input-columns
- Comma-separated list of columns to use from the input relation, or asterisk (*) to select all columns.
Parameters
model_name
Name of the model (case-insensitive).
match_by_pos
Boolean value that specifies how input columns are matched to model features:
-
true
: Match by the position of columns in the input columns list. -
false
(default): Match by name.
-
type
- A string that specifies the output to return for each input row, one of the following:
-
response
: Outputs the predicted class of 0 or 1. -
probability
: Outputs a value in the range (0,1), the prediction score transformed using the logistic function.
-
cutoff
- Valid only if the
type
parameter is set toprobability
, a FLOAT value that is compared to the transformed prediction score to determine the predicted class.Default: 0
Examples
=> SELECT PREDICT_SVM_CLASSIFIER (mpg,cyl,disp,wt,qsec,vs,gear,carb
USING PARAMETERS model_name='mySvmClassModel') FROM mtcars;
PREDICT_SVM_CLASSIFIER
------------------------
0
0
1
0
0
1
1
1
1
0
0
1
0
0
1
0
0
0
0
0
0
1
1
0
0
1
1
1
1
0
0
0
(32 rows)
This example shows how to use PREDICT_SVM_CLASSIFIER
on the mtcars
table, using the match_by_pos
parameter. In this example, column mpg
was replaced with the constant 40:
=> SELECT PREDICT_SVM_CLASSIFIER (40,cyl,disp,wt,qsec,vs,gear,carb
USING PARAMETERS model_name='mySvmClassModel', match_by_pos ='true') FROM mtcars;
PREDICT_SVM_CLASSIFIER
------------------------
0
0
0
0
1
0
0
1
1
1
1
1
0
0
0
1
1
1
1
0
0
0
0
0
0
0
0
1
1
0
0
1
(32 rows)